Gender awareness among general practitioners in France: a cross sectional study using the Nijmegen Gender Awareness in Medicine Scale (N-GAMS)

Gender is a key determinant of health and healthcare use. The question of whether physicians are aware of gender issues is important to avoid gender bias in medical practice. This study aimed to validate the Nijmegen Gender Awareness in Medicine Scale (N-GAMS) in a representative population of French general practitioners (GPs) and to analyze their gender sensitivity and the presence of gender stereotypes among them. The N-GAMS, already validated in medical students, measures gender awareness through 3 subscores: gender sensitivity (GS) and gender-role ideology towards patients (GRIP) and doctors (GRID) (gender stereotypes). After translation into French, it was distributed to 900 GPs. The scale was validated through exploratory factor analysis (EFA). Psychometric properties were tested. Multivariate linear regressions were conducted to explore the associations between GPs’ characteristics and N-GAMS subscores. EFA identified 3 meaningful factors consistent with prior theory. Subscores exhibited good internal consistency. The main findings were that GRIP was significantly higher in older physicians, in male physicians, among those who less involved their patients in decisions, and those who were not training supervisors. For GRID, results were quite similar to those of GRIP. GS was significantly higher for physicians working in health centres or medical homes and for those with gynecological practices but lower when they less involved patients in medical decisions. This study suggests that it is necessary to teach gender issues not only in medical schools but also as part of continuing medical education.


The original N-GAMS scale
The original N-GAMS scale 9 is based on two attitudinal aspects of gender-awareness: gender sensitivity (GS) and gender role ideology which is assessed towards patients (GRIP) or doctors (GRID).GS is defined as the "ability to perceive existing gender differences, issues and inequalities and incorporate these into strategies and actions" 16 .GRIP and GRID refer to gender stereotypes towards patients and doctors, respectively.These three dimensions contain 14, 11 and 8 items that GPs assessed using a 5-point Likert scale (ranging from 1 "Strongly disagree" to 5 "Strongly agree") (Table 1).Some items had reverse meaning; therefore, an adjustment of reverse scoring items was performed.The higher the item scores, the greater the gender sensitivity (GS) and gender stereotypes (GRIP and GRID).

GP recruitment
In total 3530 GPs were invited to participate by a polling company specialized in health surveys (https:// www.b3tsi.com).The recruitment of participants was conducted through e-mail and by phone.

Translation-retranslation of the N-GAMS
The English version of the original N-GAMS was translated into French by the study team and then backtranslated into English by a professional translator.The two English versions (initial and retranslated versions) were compared, item by item, by all participants and disagreements on the French version was discussed and solved (vf N-GAMS).

Exploratory factor analysis (EFA)
Given the potential uncertainty surrounding the structure of the N-GAMS scale for French practising GPs, we chose to perform an exploratory rather than confirmatory factor analysis 17 .
Appropriateness of the Spearman correlation matrix for EFA.First, we checked the appropriateness of the Spearman correlation matrix for EFA using (i) visual examination of the correlations (% of significant correlations and of correlations ≥ 0.30) 18,19 , (ii) Bartlett's test of sphericity which tests the overall significance of the correlation 20 , and (iii) the Kaiser-Meyer-Olkin measure of sampling adequacy (MSA) for the entire correlation matrix (overall MSA) and for the 33 individual items (item specific MSA).MSA values above 0.50 indicate appropriateness for performing factor analysis on the overall set of items or specific items 21 .The overall MSA quantifies the degree of intercorrelations among items, and an item-specific MSA quantifies the item's correlation with the other items in the analysis.
Determination of the number of factors to retain for rotation.Common factor analysis (iterated principal axis extraction) was used because the purpose of this study was to uncover the latent structure underlying these 33 measured items 22 .To determine the number of factors to retain, we first referred to the original validation study 9 (a priori criterion), which suggested that the scale had three dimensions.Since its development, the N-GAMS has been used several times, and researchers have extracted the same number of factors 8,[13][14][15] .We also used a visual scree test 23 supplemented by a modified latent root criterion 18 .The classical latent root criterion, also known as the Kaiser rule, is a stopping rule where all factors with eigenvalues (latent roots) greater than 1 are retained, whereas the modified version recommends that only the factors with eigenvalues greater than the average of the item-specific MSA are considered significant, which is argued to be more appropriate in a common factor analysis 18 .This criterion is usually considered reliable when the number of variables is between 20 and 50, which was the case in this study (33) and item-specific MSA above 0.40 18 .
Model acceptability.For both theoretical and empirical reasons, it was assumed that factors would be correlated 24,25 .Thus, an oblique Promax rotation with a k value of 4 was selected 26 .An oblique rotation honours the ubiquity of intercorrelations among social science variables 25 and "Promax rotation is almost always a good choice" 27 .The threshold for salience for loadings was set at 0.30 to meet the minimal level for interpretation of structure 18 , that is, variables with approximately 9% (factor loading squared) of their variance explained by the factor.
Following guidelines for model acceptability, (i) three salient item loadings (pattern coefficients) are necessary to form a factor 24 , (ii) the root mean squared residual (RMSR), which is a measure of overall residual misfit values, must be ≤ 0.08 28 , (iii) the proportion of nonredundant residual correlations greater than the absolute value Table 1.Nijmegen Gender Awareness in Medicine Scale (N-GAMS) 9 .
GS, Gender sensitivity (items scored in reverse_R) GS1_R addressing differences between men and women creates inequity in health care GS2 physicians' knowledge of gender differences in illness and health increases quality of care* GS3_R physicians should only address biological differences between men and women GS4_R in non-sex-specific health disorders the sex/gender of the patient is irrelevant GS5_R a physician should confine as much as possible to biomedical aspects of health complaints of men and women GS6_R physicians do not need to know what happens in the lives of men and women to be able to deliver medical care* GS7_R differences between male and female physicians are too small to be relevant GS8_R especially because men and women are different, physicians should treat everybody the same GS9_R physicians who address gender differences are not dealing with the important issues GS10_R in communicating with patients it does not matter to a physician whether the patients are men or women GS11_R in communicating with patients it does not matter whether the physician is a man or a woman GS12_R differences between male and female patients are so small that physicians can hardly take them into account GS13 for effective treatment, physicians should address gender differences in etiology and consequences of disease GS14_R it is not necessary to consider gender differences in presentation of complaints GRIP, Gender role ideology towards patients GRIP1 male patients better understand physicians' measures than female patients GRIP2 female patients compared to male patients have unreasonable expectations of physicians GRIP3 women more frequently than men want to discuss problems with physicians that do not belong in the consultation room GRIP4 women expect too much emotional support from physicians GRIP5 male patients are less demanding than female patients GRIP6 women are larger consumers of health care than is actually needed GRIP7 men do not go to a physician for harmless health problems GRIP8 medically unexplained symptoms develop in women because they lament too much about their health GRIP9 female patients complain about their health because they need more attention than male patients GRIP10 it is easier to find causes of health complaints in men because men communicate in a direct way GRIP11 men appeal to health care more often with problems they should have prevented GRID, Gender role ideology towards doctors GRID1 male physicians put too much emphasis on technical aspects of medicine compared to female physicians GRID2 female physicians extend their consultations too much compared to male physicians GRID3 male physicians are more efficient than female physicians GRID4 female physicians are more empathic than male physicians GRID5 female physicians needlessly take into account how a patient experiences disease GRID6 male physicians are better able to deal with the work than female physicians GRID7 female physicians are too emotionally involved with their patients GRID8 compared to female physicians, male physicians are too hurried in their consultations Vol:.( 1234567890 www.nature.com/scientificreports/ of 0.10 should be small 29 , and (iv) the results across alternative extraction (iterated principal axis, ordinary least squares, weighted least squares, minimum residual) and rotation methods (promax, oblimin) must be robust.

Item reliability
Item reliability was assessed through two diagnostic measures of internal consistency.First, a Cronbach's alpha coefficient was calculated for each sub-scale.It should be at least 0.70.Second, for each subscale, item-rest score correlations between the items and the rest scores of the subscale (i.e., the score computed from the items of the dimension deleting that item) were computed, using Spearman correlations.The absolute value of the item-rest correlations should be above 0.1.Absolute values between 0.1 and 0.3 are considered "fair", while those above 0.3 are deemed "good" 20 .

Bivariate correlations between the subscores
Bivariate correlations between the dimensions were also conducted.p values were adjusted for multiple comparisons with the Holm method.

Descriptive analysis
We first performed a descriptive analysis of GPs' characteristics and scores on the NGAMS by dimension.We used the so called « dummy » coding for all categorical variables, and age has been segmented into 4 classes.For a GP, the score in a dimension (called the subscore) was obtained by averaging the observed values of the items in the dimension.Mean scores (95% confidence interval) for the NGAMS by dimension were calculated.

Linear regressions
The relationship between GPs' characteristics and subscores was analysed through univariate linear regressions.GPs' characteristics with a p value at 0.2 or less were included in multiple linear regression models.A value < 0.05 was considered statistically significant.

Ethics statements
This study was approved by the the Inserm Ethics Evaluation Committee (Comité d'évaluation éthique de l'Inserm), under the 22-895.We confirm that informed consent to participate was obtained from all of the participants in the study and that all methods were performed in accordance with the relevant guidelines and regulations.

Results
A total of 3530 GPs were contacted (3454 received a link via the internet, and 76 were contacted by phone).Of these, 2479 refused to answer (2425 and 54, respectively).The response rate was 30%.Of the 1051 respondents, 151 had incomplete questionnaires.The study population was 900 GPs.

Translation-retranslation of the N-GAMS
The vf N-GAMS is available upon request.

Exploratory factor analysis (EFA)
Appropriateness of the data for EFA.Inspection of the correlation matrix reveals that 366 of the 528 correlations (69%) were significant at the 0.01 level, and 168 of the 528 correlations (32%) were ≥ 0.30.Bartlett's test of sphericity rejected the hypothesis that the correlation matrix was an identity matrix (Bartlett χ 2 (528) = 12,708.279,p < 0.001).Therefore the correlation matrix contained statistically significant correlations.The overall MSA value fell in the meritorious range (above 0.80) with a value of 0.938.Examination of the item-specific MSA values for each variable yielded a range from 0.68 to 0.97, with 31 out of 33 MSA values above 0.80, and an average of 0.91.Taken together, these measures indicate that our data were appropriate for EFA.
Determination of the number of factors to retain for rotation.The average of the item-specific MSA was 0.91.Three factors had eigenvalues greater than the average of the MSA. Figure 1 indicates that both latent root and scree test criteria suggest retaining 3 factors, confirming the a priori criteria.
Model acceptability.Table 2 shows the results of the EFA.The measured items were distributed across the three factors as predicted by prior theory and the structure was interpretable and theoretically meaningful.One item, GRIP 11, was under the limit for saliency (0.22); three items did not load sufficiently on their own dimension GRID 3 (0.19), GRID 5 (0.20) and GRID 6 (0.14), but on the GRIP dimension (with loadings > 0.30).These items were removed.Two items (GS2 and GS13) had loadings at the limit of saliency (0.29), but we retained them as Hair et al. 18 suggested that for a sample size of n = 350, the threshold for loading saliency is 0.30.The sample size of our study was n = 900; therefore, a loading of 0.29 clearly meets the minimal level for the interpretation of structure.In summary, 4 loadings (14%) met the minimal level for the interpretation of structure (0.29-0.40), 15 loadings (52%) were practically significant (0.40-0.70), and 10 loadings (34%) were indicative of well-defined structure (> 0.70).Altogether, the three latent factors accounted for 41.52% of the total variance of the original data.The first factor (GRIP) explained 25.99% of the total variance, the second factor (GS) explained 11.49%, and the third factor (GRID) explained 4.04% of the total variance.RMSR was low at 0.036, and only 4 (0.99%) of the residuals were above the absolute value of 0.10, indicating no presence of another factor.
The results across alternative extraction and rotation methods were robust (i.e., gave similar solutions).Factor analysis on different subsamples (gender, age) also gave similar solutions.
Twelve GS items out of 14 (86%), 100% of GRIP items and 100% of GRID items had an item-rest correlation greater than 0.30.

Bivariate correlations between the subscores
The GRIP score and GRID score were positively correlated ( r = 0.611; p < 0.001), no significant correlation was found between the GS score and GRID score ( r = − 0.027; p = 0.426), and no significant correlation was found between the GS score and GRIP score ( r = − 0.066; p = 0.096).

Descriptive analysis
The 900 recruited GPs were representative in terms of age, sex and urban/rural practice of the general population of GPs in France.Their characteristics are summarized in Table 3. Scores for the NGAMS by dimension are presented in Fig. 2. The mean GS, GRIP, and GRID scores were 3.23 (3.18-3.27),2.33 (2.28-2.39)and 2.46 (2.40-2.51),respectively.GS items were scored 3 or more in 69% of cases, which suggests medium to high gender sensitivity, while GRIP and GRID items were scored 4 or 5 in 17.4 and 19.8% of cases, respectively reflecting significant gender stereotypes towards patients and doctors in this population.The descriptive statistics of the N-GAMS items for all study populations and by sex are summarized in Tables 4 and 5.

Linear regressions
The results of the univariate linear regressions are presented in Table 6.The following variables sex, age, type of exercise, training supervisor, number of years of practice, gynecological practice, patients involved in medical decision which had a p value less than 0.2 in at least one of the three models were included in multiple linear regression models.In the multivariate analysis (Table 7), gender sensitivity was lower for doctors who did not involve their patients at all or involved them moderately in medical decisions than for those who involved them a lot (p = 0.007) and was higher for doctors working in settings other than private practices (p = 0.049) and for those with gynaecological practice (p = 0.036).Gender stereotypes towards patients were significantly more important the older the doctors were, with an increasing gradient of GRIP scores (p < 0.001).They were also higher among male doctors than among female doctors (p = 0.023), among those who did not involve or moderately involved their patients in decisions (p = 0.01) and among those who were not training supervisors (p = 0.05).Gender stereotypes towards doctors were also associated with age (p < 0.001) and were higher among those who did not involve or moderately involved their patients in decisions (p = 0.014).They were lower among male doctors than among female doctors (p < 0.001).

Discussion
We validated the NGAMS in a population of French GPs and used this scale to analyse GPs' gender awareness in this population.We showed that GS was positively associated with care practices (involving patients more in decisions, and working in health centres (centres de santé) or medical homes (maisons de santé pluriprofessionnelles) compared with working in private practice), and practising gynaecology), while GRIP, although also positively associated with care practices (not at all/little/moderately involving patients in the decision, and not being training supervisors), was also associated with GPs' sociodemographics (being male, older).For GRID, results were quite similar to those of GRIP, except that male doctors had fewer gender stereotypes towards doctors than female doctors.www.nature.com/scientificreports/An EFA of the N-GAMS instrument's items was used to identify the latent structure underpinning the instrument's 33 items.Although 9 reported using principal component analysis, we chose to use principal axis factoring instead as it appears to be a particularly suitable means of extracting latent factors based on the shared variance of the variables 22 .The final set of 29 accepted items produced a 3-dimensional structure of gender awareness: GS (14 items), GRIP (10 items), and GRID (5 items).These three subscales had satisfactory internal consistency (alpha > 0.80).We found a quite high association between the GRID and GRIP subscales, similar to other authors suggesting a common ground for GRIP and GRID.However, the data did not show any evidence of correlation between GS and the other two subscales, which also supported earlier findings 9,14 .This indicates that these are separate aspects of the attitudinal component of gender awareness, which may need to be targeted and addressed independently in interventions 14 .

Table 2. Exploratory factor analysis of the N-GAMS (n = 900 general practitionners). N-GAMS Nijmegen
Gender Awareness in Medicine Scale.Significant loadings are bold.

GS GRIP GRID
GS, Gender sensitivity (items scored in reverse R) GS12R Differences between male and female patients are so small that physicians can hardly take them into account 0.65 − 0.07 − 0.02 www.nature.com/scientificreports/ The N-GAMS has never been validated among GPs.Therefore, there are no comparative measures of gender awareness in this population.It should be noted that the sample of 900 GPs we surveyed was representative in terms of age, gender, rural/urban practice and type of practice (private surgery/others) of GPs in France 30 .
With regard to GS, the result we found of an independent association of three variables describing care practices, i.e., involving patients in decisions, practising gynaecology, and working in health centres or medical homes, with GS is original.Its originality lies both in the fact that it has never been shown before and in the interpretation that could be drawn from it, namely, that these associations could be mediated by patient-centred practices.Following Lindsay et al., GS is a key component of patient-centred care 31 .Applying a gender-sensitive perspective in patient-centred care requires that healthcare providers can perceive existing sex and gender differences, issues and inequalities and incorporate these into strategies and actions.The patient-centred approach applied to ambulatory care 32 implies respect for the patient's values, preferences, and expressed needs, information and education, access to care, emotional support to relieve fear and anxiety, involvement of family and friends, continuity and secure transition between health care settings, physical comfort, and coordination of care.In this framework, shared decision making (i.e., when the patient is involved to reach the optimal decision) is seen as the pinnacle of patient-centred care 33 .Moreover, prior experiences, notably with patient-centred care medical homes in the US, show that these healthcare organizations should allow better monitoring of the care provided to ensure that it corresponds to the best standards, increase the possibilities of interaction and communication with patients, to encourage their participation in the care process, and better coordinate the intervention of the various stakeholders in the care process 32 .This is the equivalent of the multiprofessional health centres in France, whose number is increasing.The GPs who work in these healthcare organizations are part of this process of providing patient-centred rather than disease-centred care, even if the organizational practices needed to implement and adopt patient-centred care remain incomplete 34 .Finally, regarding OB/GYN practices, developmental issues such as menstruation, contraceptive initiation, pregnancy, childbirth, and menopause that are addressed by GPs can be transitional periods of difficulty such as unwanted pregnancy, infertility, pregnancy loss, chronic illness and pain, mood and sleep disorders, interpersonal trauma, and poverty, and may serve as opportunities to address the complexity of patients' needs 35 , reflecting the interest of these physicians in the patient-centred approach 32 .
With regard to GRIP, and the association between being a male doctor and having more gender stereotypes, in four of the NGAMS validation studies conducted among medical students 8,9,13,15 , male medical students held stronger gender stereotypes than female medical students.These findings may explain, at least in part, the effects of patients' and physicians' gender discordance on patient management observed in general practice.Indeed, several studies conducted in general practice have shown that the management of female patients by male doctors (as opposed to female doctors) may be detrimental in the area of cancer screening for women in the USA 36 , health promotion (advice on physical exercise and weight loss) and the management of hypertension in France 37,38 , or physicians' perception of uncertainty about a diagnosis and hidden agenda beyond the reason(s) for the visit www.nature.com/scientificreports/theoretical and practical teaching system 15 .It is not clear from our study whether stereotypes towards patients are the result of an ageing effect or a cohort effect.Indeed, given that the oldest GPs we interviewed belonged to the 1943-1956 birth cohort (aged 66-79 years in 2022) while the youngest belonged to the 1982-1995 cohort (aged 27-40 years in 2022), it can be assumed that growing up during such distinctive historical times influenced gender stereotypes towards patients 40 .There are no data in the literature to support this hypothesis.We would need longitudinal data to disentangle these ageing and cohort effects.Additionally, gender stereotypes towards patients increased when GPs did not their patients at all, little or moderately in medical decisions, with a mean GRIP score ranging from 2.13 (patients systematically involved) to 2.57.This result is consistent with those in the literature.Within the framework of an ecological model of communication in medical encounters, Street 41 stated that gender-based perceptions and stereotypes can play a prominent role in medical encounters, although, we still know very little about the scope of these beliefs and their impact.Sandhu et al. 42 further claimed that non concordant gender dyads may be characterized by perceived differences in power, status, dominance, gender stereotypes, and attitudes towards the other sex that may lead to higher levels of tension and a lower communication quality.In a study performed in primary care where the consultations were videotaped, the provision of patient-centred care (measured by coding the videotapes using the Davis Observation Code) was shown to be influenced by gender concordance: female concordant dyads were associated with a greater amount of patientcentred care 43 .Finally, not being a training supervisor was associated with more gender stereotypes towards patients with a mean GRIP score ranging from 2.16 (being a training supervisor) to 2.39.This result, which to our knowledge, has not previously been reported, could be explained in several ways.GPs who choose to be

Conclusion
This study is the first to measure gender awareness in a population of GPs.All the results discussed above allow us to conclude that it seems necessary to teach gender issues in medical schools.This is already the case in some countries, such as Sweden and Switzerland.We may perhaps go further by suggesting that gender be taught as part of continuing medical education. https://doi.org/10.1038/s41598-024-56396-5
Figure 2. Distribution of item values and mean scores for the NGAMS by dimension.Vol.:(0123456789)Scientific Reports | (2024) 14:5733 | https://doi.org/10.1038/s41598-024-56396-5www.nature.com/scientificreports/ in New Zealand 39 .Our results also show that, all other things being equal, gender stereotypes towards patients increase with the age of the GP, with a very clear gradient, with a mean GRIP score from 2.09 (between 27 and 40 years old) to 2.54 (between 66 and 79 years old).Looking at the validation studies of the N-GAMS among medical students, the results of the effect of age on gender stereotypes towards patients vary from one study to another.In multivariate linear models, stereotypes towards patients decreased linearly with students getting older in Switzerland (ranging from 18 to 32 years old) (coefficient − 0.03, p = 0.035) (Rrustemi et al.) and in Sweden (coefficient − 0.189, p < 0.001) (Andersson et al.).In contrast, older students expressed more stereotypical thinking about patients in Italy (coefficient 0.04, p value = 0.012) 15 .No significant relationships were found in Portugal 14 .As Bert et al. suggested, Swedish and Swiss medical students reduced their stereotypes probably due to a good

Table 4 .
Descriptive statistics of the N-GAMS (n = 900 general practitionners).N-GAMS Nijmegen Gender Awareness in Medicine Scale.

Table 5 .
Descriptive statistics of the N-GAMS by sex (n = 900 general practitionners).N-GAMS Nijmegen Gender Awareness in Medicine Scale.